Mohd. Fua'ad Rahmat

Modeling and controller design of an industrial hydraulic actuator system in the presence of friction and internal leakage

This paper presents a robust controller scheme and its capabilities to control the position tracking performance of an electro-hydraulic actuator system. Sliding mode control with fixed and varying boundary layer is proposed in the scheme. It is aimed to compensate nonlinearities and uncertainties caused by the presence of friction and internal leakage. Its capabilities are verified through simulations in Matlab Simulink environment. The friction was represented by the LuGre model and the internal leakage was assumed to change. The results indicate that the scheme successfully improves the robustness and the tracking accuracy of the system. This improvement offers a significant contribution in the control of modern equipment positioning applications.

Nonlinear PI Control with Adaptive Interaction Algorithm for Multivariable Wastewater Treatment Process

The wastewater treatment plant (WWTP) is highly known with the nonlinearity of the control parameters, thus it is difficult to be controlled. In this paper, the enhancement of nonlinear PI controller (ENon-PI) to compensate the nonlinearity of the activated sludge WWTP is proposed. The ENon-PI controller is designed by cascading a sector-bounded nonlinear gain to linear PI controller. The rate variation of the nonlinear gain is automatically updated based on adaptive interaction algorithm. Initiative to simplify the ENon-PI control structure by adapting has been proved by significant improvement under various dynamic influents. More than 30% of integral square error and 14% of integral absolute error are reduced compared to benchmark PI for DO control and nitrate in nitrogen removal control. Better average effluent qualities, less number of effluent violations, and lower aeration energy consumption resulted.

Particles flow identification in pipeline using adaptive network-based fuzzy inference system and electrodynamic sensors

Purpose – An identification model for materials flow through a pipeline is presented in this paper. The development of the model involves fuzzy C-means clustering, in which different flow regimes can be identified by every adaptive network-based fuzzy inference system (ANFIS). The paper aims to discuss these issues. Design/methodology/approach – For experimentation, 16 electrodynamic sensors were used to monitor and measure the charge carried by dense particles flow through a pipeline in a vertical gravity flow rig system. Four ANFIS models were also used simultaneously to provide the expected output on thresh-holding and were evaluated for ten different flow regimes, which produced satisfactory results at high flow rate. Findings – The observations made on the four ANFIS models in the flow identification experimentation (in ten different flow regimes) have shown convincing and satisfactory results at high-flow rate of the particles. Originality/value – Electrodynamic sensors have shown strong sensing cap...

Controller design for position tracking of nonlinear system

Usually, the nonlinearities existing in the system is eliminated by using linearization method. However, backstepping method allows additional nonlinearities to be created and introduced to the control process so that the undesirable nonlinearities can be cancelled out from the system. In this work,position tracking of electrohydraulic actuator system is taken as a numerical example since it is highly nonlinear. Backstepping controller is designed for the system without disturbance and with additional disturbance is given to its actuator. Control parameter of the designed controller for both condition is then optimized by using Particle Swarm Optimization method. The performance of the designed controller to the system is observed through its tracking error.